Facilitating person-centered patient participation in kidney care—a process evaluation of a quasi-experimental study incorporating a tool and training of local implementation teams
Bibliographic record
Abstract
Abstract Background The transfer of innovations into healthcare is laden with challenges. Although healthcare professionals are expected to adopt and fulfil new policies, a more person-centered healthcare with conditions for preference-based patient participation is anticipated. Methods The aim of the study was to evaluate two implementation strategies for person-centered patient participation in kidney care, including dissemination of a clinical toolkit, and additional training and support of internal facilitators. Nine Swedish kidney care units joined the study (August 2019–September 2021), strategically organized into: a control group (three sites, no support); a standard dissemination group (three sites, with a tool for patient participation and guidance disseminated to the site managers); and a facilitated implementation group (three sites, with the tool and guidance disseminated as above, plus a six-month support program for designated internal facilitators). This process evaluation was comprised of repeat interviews with managers (n = 10), internal facilitators (n = 5), recordings, and notes from the interventions, and Alberta Context Tool survey data (n = 78). Hybrid analyses comprised mixed methods: descriptive and comparative statistics, and qualitative descriptive analysis. Results None of the control group sites addressed patient participation. While the standard dissemination sites’ managers received and appreciated the toolkit, they made no attempts to make further use of it. In the facilitated implementation group, five internal facilitators from three sites engaged in the support program. They welcomed the opportunity to learn about preference-based patient participation, and about implementation, including potentially enhanced opportunities for preference-based patient participation via the tool. Each site’s facilitators developed a separate strategy for the dissemination of the tool: the tool was used with a few patients in each site, and only some staff were involved. Although noting a general interest in improving patient participation, the internal facilitators described limited local support. Rather, they suggested a longer support program and more local backing and engagement. Conclusions Facilitating person-centered patient participation is complex, given the need to address attitudes, beliefs, and behaviors. This study indicates slow uptake and change, and more efficient strategies are needed to ensure the fundamentals of care remain accessible to all.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".